Network-based positioning is based on measurements taken from available communications networks, such as cellular networks and wireless local access networks (WLAN). Depending on the signaling structures in the network, measurements used for the positioning can be Received Signal Strength (RSS), propagation delay, Angle Of Arrival (AOA), Round-Trip Time (RTT), or any other measurement that is applicable for positioning purposes.
Typically, the network based positioning is divided in two stages. In a training stage, learning data is collected. The data may be collected in the form of fingerprints that are based on measurements of mobile devices. A fingerprint may contain a location estimate and measurements taken from the radio interfaces. The location estimate may be for example global navigation satellite system (GNSS) based, sensor-based, WLAN-based, or manually inputted. If the measurements taken from the radio interfaces are, by way of example, RSS measurements, the measurements may comprise for instance an RSS value in dBm, where the Doppler effect (fast fading) has been averaged out, timing measurements (e.g. RTT), an identification of a base station or of a WLAN access point, a Cell ID in cellular networks and Medium Access Control (MAC) addresses, Service Set Identifiers (SSID), etc., in WLANs. The training can be a continuous background process, in which mobile devices are continuously reporting measured data to the server or learn their radio environment internally offline. In an estimation/positioning stage or data estimation stage, a mobile device may estimate its current location based on the data or a subset of data that is available from the training stage.
If the data is collected by a server, the collected measurement data may be uploaded to a database in the server or in the cloud, where algorithms may be run to generate models of radio communication nodes for positioning purposes. Such models may be coverage areas, node positions, radio propagation models, etc. In the end, these models or parts of them may be transferred to mobile devices for use in position determination. Alternatively, the models may be stored in a positioning server to which the mobile devices may connect to for obtaining position information.
One considerable difference between indoor and outdoor positioning is the importance of vertical direction. In outdoor positioning it is often enough to achieve horizontal position estimates using a two-dimensional map, whereas indoors, especially in tall buildings, it may be essential to have a capability to estimate also the user floor. This leads to a three-dimensional data processing both in the data collection stage and the positioning stage.